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A Swarm Inspired Probabilistic Path Selection with Congestion Control in MANETs

机译:MANETs中具有拥塞控制的群体启发概率路径选择

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Congestion is a major problem in mobile ad-hoc networks. In mobile ad hoc networks congestion creates delay in transmission and also loss of the packet that causes wastage of time and energy on recovery. The Wireless Networks have to play an important role to adopt and execute a large no of innovative application. New challenges have come considering the major limitations of the ad hoc network like node's limited processing power, balance the load of network (to maintain the computation of the node). To overcome the above problem some algorithm is invoked and there may be huge amount of packet loss and this leads to decrease the lifetime of the network. The objective of our proposed algorithm is to identify the congestion areas between source and its neighboring nodes to the destination and thus it will help to avoid the congestion of the network in the intermediate links and also minimize the packet loss in the network. Using a new mathematical model considering the swarm-based ant intelligence concept, we found an efficient congestion control mechanism (Ant's probabilistic transition rule).
机译:拥塞是移动自组织网络中的一个主要问题。在移动自组织网络中,拥塞会造成传输延迟,还会造成数据包丢失,从而浪费时间和精力进行恢复。在采用和执行大量创新应用程序时,无线网络必须发挥重要作用。考虑到ad hoc网络的主要局限性(例如节点的有限处理能力,平衡网络的负载(以维护节点的计算)),新的挑战已经来临。为了克服上述问题,调用了一些算法,并且可能存在大量的分组丢失,这导致网络寿命的减少。我们提出的算法的目的是识别源和它的邻近节点到目的地之间的拥塞区域,因此它将有助于避免中间链路中网络的拥塞,并使网络中的数据包丢失最小化。使用考虑了基于群的蚂蚁智能概念的新数学模型,我们发现了一种有效的拥塞控制机制(Ant的概率转移规则)。

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